Operational
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- •Design, develop, and support data solutions using Azure platform to enhance operational efficiency and data integrity.
- •Utilize expertise in Python, PySpark, and SQL to analyze complex datasets and generate insightful reports that drive improvements in client operations.
- •Implement configurations and develop technical solutions that automate processes and ensure seamless integration of data across various cloud platforms.
•Functional
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- •Build ETL workflows and automate data pipeline tasks using Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and AWS Glue.
- •Develop scripts and automation tools for data ingestion and transformation, leveraging PySpark and other libraries to streamline processes.
- Create and manage robust data processing applications, ensuring effective
Strategic
•Collaborate with cross-functional teams to identify and implement process improvements, driving standardization and efficiency in data operations.
•Contribute to the development of technical strategy that aligns with business goals, enhancing data-driven decision-making capabilities.
•Client Interactions
•Work with global stakeholders to understand their data needs and develop customized solutions using Azure and AWS platforms.
Communicate complex technical concepts clearly to non-technical stakeholders, ensuring alignment with strategic objectives and business requirements.
Educational qualifications
- •Minimum Qualification Required: B. Tech/MBA from a recognized Tier-1 institute
- •Professional Certifications Required: Data Engineer Certifications
- Work experience
- •Total Number of Years of Work Experience: 4+ years
- •Relevant Number of Years of Work Experience Required: 4+ Years
- •Special Call Outs on the Nature of Work Experience: Experience in client-facing roles with demonstrated skills in business process improvement and technology implementation. (Preferably from Big 4 or other consulting firms)
Job description provided by KPMG Global Services.
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